The newly-established Khalifa University of Science and Technology combines the Masdar Institute
of Science and Technology (MI), Khalifa University of Science, Technology and Research
(KUSTAR), and the Petroleum Institute (PI) into one world-class, research-intensive institution,
seamlessly integrating research and education to produce world leaders and critical thinkers in
applied science and engineering.

The Masdar Institute of Science Technology and Petroleum Institute remain as research institutes
at Khalifa University, playing a critical role in the research structure and culture of the university
and serving as interdisciplinary research units focused on long-term strategic priorities.

Research is at the core of KU, as we know research has the power to transform industry, society
and regions KU’s research-focused academics seek to achieve global impact through excellence
in research domains of regional importance.

PhD in Engineering

PhD in Engineering

The aim of the Ph.D. in Engineering program is to produce graduates able to conduct research independently at the highest level of originality and quality.

The PhD in Engineering degree is awarded for candidates who successfully complete the taught courses and research components of the program . The students are required to complete a program of advanced courses in engineering. The students are also required to carry out an independent investigation of a specialized area of engineering. Candidates for this degree are supervised by experienced researchers and are expected to demonstrate initiative in their approach and innovation in their work. Ph.D. Candidates prepare and present a thesis on their chosen area. Research may be undertaken in several topics corresponding to the areas of focus identified by the University.

A candidate applying to the program may opt to apply for a generic PhD in Engineering (i.e., with no one specialization) or for a PhD in Engineering with a specialization in one of the following areas: Aerospace Engineering, Biomedical Engineering, Electrical and Computer Engineering, Mechanical Engineering, Nuclear Engineering, Robotics

Provide graduates with good understanding of the research environment and its requirements

Equip graduates with personal effectiveness skills

Produce graduates who will make substantial contributions to academics, industry, business, and the community

Undertake and publish research that is relevant to industry and business, and is highly regarded by the international community

Program Outcomes

A student graduating with a Ph.D. in Engineering degree will be able to:

Demonstrate a high level of understanding and specialization in his/her field of study

Conduct independent investigation with rigour and discrimination

Acquire and collate information through the effective use of appropriate sources and equipment

Show an appreciation of the relationship of the area of his/her research to a wider field of knowledge

Demonstrate a critical appreciation of the literature in his/her area of research

Demonstrate an ability to recognise and validate research problems

Demonstrate an understanding of relevant research methodologies and techniques and their appropriate application to his/her research

Apply effective research project management techniques

Make a significant and original contribution to the body of knowledge in his/her field of study

Demonstrate an ability to appraise critically his/her contribution in the context of his/her overall investigation

Constructively defend his/her research outcomes

Write clearly, accurately, cogently, and in a style appropriate to purpose

Construct coherent arguments and articulate ideas clearly to a range of audiences

Show awareness of relevant research issues including environmental, political, economical, social, copyright, ethical, health and safety, exploitation of results, and intellectual property rights

Demonstrate personal effectiveness attributes including initiative, motivation, flexibility, self-discipline, self-reliance, and the capacity to work independently

Career Opportunities

A PhD in Engineering opens a wide range of career opportunities in academia and industry. Graduates can pursue academic careers in educational institutions or research careers in academic/industrial research labs or Research & Development centers. PhD in Engineering graduates can also find excellent opportunities in government organizations, science/engineering policy and funding agencies, and in institutions that deal with Technology Transfer, Patents, and Intellectual Property management. In addition, a PhD in Engineering opens many opportunities in consultancy services and entrepreneurship.

In particular, the disciplines of Aerospace, Biomedical, Electrical and Computer, Mechanical, Nuclear, and Robotic engineering touch virtually every aspect of human lives. These disciplines sit at the core of most technical advances being made on daily basis.

A candidate applying to the program may opt to apply for a generic PhD in Engineering (i.e., with no one specialization) or for a PhD in Engineering with a specialization in one of the following areas:

Aerospace Engineering (AERO)

Biomedical Engineering (BMED)

Electrical and Computer Engineering (ECCE)

Mechanical Engineering (MECH)

Nuclear Engineering (NUCE)

Robotics (ROBO)

Each of the above specializations may set specific constraints to be imposed on the discipline of the candidate’s Master degree to be acceptable for admission to the specialization. Disciplines acceptable for admission to each specialization are listed below:-

The list of disciplines related to a given specialization is an indicative list rather than an exclusive/exhaustive list. Candidates with Master degrees in other pertinent disciplines may also be considered. In such cases, candidates will be asked to submit course descriptions along with their transcripts.

A candidate applying to be considered for a generic PhD in Engineering (i.e., with no one specialization) must satisfy the admission requirements of at least one of the specializations.

In addition, candidates must have sufficient prior background to meet the prerequisites of the program. In particular, candidates must have achieved a minimum level of proficiency in mathematics in the form of a grade of B or better in at least one graduate-level mathematics course or an equivalent score on a university-administered mathematics proficiency test.

Program Duration

The minimum period of study will be 3 years from the date of first registration in the case of full-time registration and 5 years from the date of first registration in the case of part-time registration. This study period includes the time taken to write-up the thesis.

The maximum period of study will be 5 years from the date of first registration in the case of full-time registration and 8 years from the date of first registration in the case of part-time registration. This study period includes the time taken to write-up the thesis. In exceptional cases, an extension of registration may be granted.

Program Components

The Ph.D. in Engineering program consists of two main components:

Taught Courses Component: In this component the student is required to complete a program of advanced study.

Research Component: In this component the student is required to carry out an independent investigation of a specialised area of engineering.

For the award of the Ph.D. in Engineering degree, the student must satisfy the following requirements:

Courses: The student must satisfy the taught courses requirements of the program.

Research Proposal: Having satisfied the taught courses requirements of the program, the student is then required to prepare a research proposal and pass a research proposal examination before being allowed to progress further on the program.

Thesis:The student must then complete a thesis on original research and defend it successfully in a viva voice examination.

Selected topics in current research interests not covered by other courses. Contents will be decided by the instructor and approved by the Graduate Studies Committee. The Course may be repeated once with change of contents to earn a maximum of 8 credit-hours.

Module 1 – Cardiac Regeneration: This module will review the cellular implications of myocardial infarction injury, the regenerative capacity of amphibian and fish, the limited regenerative capacity of rodent hearts, and the evidence for the limited human cardiac regeneration. It will also present particular state of the art cell-based approaches for achieving cardiac regeneration including utilization of cardiac progenitor cells, bone marrow cells, pluripotent stem cells, direct cell reprogramming, and tissue engineering applications. Module 2 – Advanced Drug Delivery Systems: The objective of this topic is to immerse the students in the fundamental and application of advanced drug delivery systems using biomaterials. The following topics will be included biomaterials, formulation techniques, comparison of delivery systems, and the routes of drug administration. Approaches will focus on non-viral gene and protein delivery systems, and applications to gene therapy. Module 3 – Cytoskeletal mechanics: This topic will cover recent progress towards an integrated understanding of the cytoskeleton. The module will focus on three concepts: (1) long-range order arises from the regulated self-assembly of components guided by spatial cues and physical constraints; (2) architecture of the cytoskeleton controls the physical properties of the cell; and (3) cytoskeletal links to the external microenvironment can mediate both short- and long-timescale changes in cellular behavior. Module 4 – Strategies for Genetic Engineering: This module will focus on two major strategies designed to direct the fate of abundant cell types into desired, but difficult to obtain, populations: (1) directed differentiation, in which cultured pluripotent stem cells are coaxed through a series of steps that are usually designed to mimic those that produce the desired cell type in vivo; and (2) reprogramming, in which one fully differentiated cell type is converted directly into another without a multipotent or pluripotent intermediate; methods that can be used to compare various parameters in cells created in vitro with those of cells produced by normal development in vivo. Module 5 – Genome-wide association studies: Genome-wide association studies (GWAS) promised to greatly enhance our understanding of the genetic basis of common and complex diseases using chips that can capture information from more than two-thirds of the common variation in the human genome. This module will review literature dealing with the development and utilization of this technology. In particular, it will focus on the usage of this technology for the analysis and understanding of how the genotype affects the phenotype of certain diseases including type 2 diabetes and cardiovascular disease. Module 6 – Cellular Microenvironment: The cell microenvironment holds vital biochemical and biophysical cues that ensures cell fate, development, and plasticity. This module focuses on (1) different categories of biochemical and biophysical cues, (2) mechanisms for the internalization of biochemical cues and the mechanotransduction of biophysical cues, and (3) biophysical cues due to extracellular matrices and external forces. These focus points will be delivered with close reference to state of art case studies in tissue rengeration. Module 7 – Microfluidics in Biology and Medicine: This module introduces microfluidics and how the behavior, precise control and manipulation of fluids and can be used to advance research in biology and medicine. The module will cover selected roles of microfluidics and their influence in the study of drug encapsulation for targeted delivery, cell-cell interaction, cellular dynamics, cellular signaling, tissue development and cellular behavior.

Prerequisite – Prior course work and/or research experience in human physiology and in systems engineering

Module 1 – Experimental techniques: This module reviews the associated experimental techniques to obtain information regarding genetic sequences, protein synthesis and metabolic/cellular response of living systems. The aim is to introduce the vast array of techniques available for multi-scale research into biology and medicine, embracing the potential of each, while acknowledging their disadvantages. Module 2 – Bioinformatics and analysis of experimental data: The information gathered from experimental biological systems research is multivariate, with miniscule differences, often clouded with inherent noise. Here, data-sieving/data-mining methods and analysis of data generated by powerful experimental techniques will be introduced, such that results can be used with confidence. Module 3 – Computational models of molecular/cellular systems. Computational biology provides tools for predictive modeling and/or systems modeling. This modules showcases, through case studies, the development and application of both data-driven and full fledge theoretical models. Module 4 – Bioinformatics in drug discovery and development. Bioinformatics provides a tool to get to a structure through sequence; while structure- aided drug design offers a means to get to a drug through structure. Computational chemistry will be combined with biology to understand, predict, and evaluate a drug target and design a drug candidate.

Selected topics in current research interests not covered by other courses. Contents will be decided by the instructor and approved by the Graduate Studies Committee. The Course may be repeated once with change of contents to earn a maximum of 8 credit-hours.

ECCE 702 is designed to provide an in-depth understanding of advanced technologies for digital communication systems, and to enable the student to relate these technologies to current and future generation communication systems.

Selected topics in current research interests not covered by other courses. Contents will be decided by the instructor and approved by the Graduate Studies Committee. The Course may be repeated once with change of contents to earn a maximum of 8 credit-hours.

Selected topics in current research interests not covered by other courses. Contents will be decided by the instructor and approved by the Graduate Studies Committee. The Course may be repeated once with change of contents to earn a maximum of 8 credit-hours.

Prerequisite – Students should have a fundamental understanding of the requirements for radiological environmental impact assessment.

Review of Radiation Detection and measurement: Nuclear structure, nuclear stability and radioactive decay. Nuclear detectors and Survey instruments. Radiation and Environmental Protection: Study of the natural and man-made sources of radiation in our life (living and working environment) and the doses they cause. The Natural Radiation in the Environment: Cosmic radiation, air travel, cosmogenic radionuclides, terrestrial external radiation, Internal exposure, Radon and Thoron. Medical Exposure: Diagnostic Radiology, Nuclear Medicine, Radiotherapy. Radioecology: dispersion and transfer of radiation in the terrestrial environment; dispersion and transfer of radiation in the aquatic environment; effects of ionizing radiation on terrestrial and aquatic organisms; effects of ionizing radiation on ecosystems; assessment of radiological impact of releases on the environment; measurement of radioactive releases and countermeasures; decision aiding techniques. Occupational Exposure: Nuclear and general industry. Biokinetics: study of the cell, the nervous system, the cardiovascular, anatomy and other organs of the body and how intake of radionuclide in some of these organs will distribute and behave. Study of ionizing and Non-ionizing radiation: exposure, dose, low/high level radiation and health effect. Models for the Biokinetics and Dosimetry of Radionuclides: The respiratory tract (RT) Model: analyze the RT model and understand how it is compartmentalized. Use model to calculate doses in air as well as unit intake, deposition of radiation in each compartment and retention. Also distinguish between particle sizes and deposition using the same model as well as particle clearance. Gastrointestinal Tract (GIT) Model: analyze the (GIT) model and how it is compartmentalized. The Bone models: distinguish between bone surface and bone volume radiation seekers. Introduce Models for the embryo. Biokinetics and Dosimetry for selected Radionulcides. Study certain nuclides as applications of models.

This course provides students with practical knowledge of the requirements and principles of nuclear safety regulation and safety justification to ensure safe operation and supervision of the reactor plant through safety analysis report (design control document).

ROBO 701 – Control of Robotic Systems (4-0-4)

Prerequisite – Engineering Mathematics and Computation.

Basic concepts and tools for the analysis, design, and control of robotic mechanisms. Kinematics, statics and dynamics of robotic Systems: Kinematics of Robotic Systems, Statics of Robotic Systems, Dynamics of Robotic Systems. Trajectory planning based on mechanics: General Cases, Grasp mechanics, Multi-finger grasping. Control of robotic systems: Control of Robotic Systems, Non-Linear Control, Multi-Variable Control of Robotic Systems, Robust control and adaptive control of Robotic Systems, Force and Impedance Control Robotic Systems, Interaction Control Robotic Systems.

Selected topics in current research interests not covered by other courses. Contents will be decided by the instructor and approved by the Graduate Studies Committee. The Course may be repeated once with change of contents to earn a maximum of 8 credit-hours.